Monday, November 06, 2023

 

What happens when cats get fat? Scientists weigh in


Peer-Reviewed Publication

UNIVERSITY OF ILLINOIS COLLEGE OF AGRICULTURAL, CONSUMER AND ENVIRONMENTAL SCIENCES

cat eating dry food from a bowl 

IMAGE: 

WHEN CATS OVEREAT AND GAIN WEIGHT, IT AFFECTS THEIR DIGESTIVE SYSTEM AND GUT MICROBIOTA, UNIVERSITY OF ILLINOIS RESEARCHERS FOUND.

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CREDIT: LAUREN QUINN, UNIVERSITY OF ILLINOIS.




URBANA, Ill. – Cat owners want Kitty to be happy, but providing an abundance of food and snacks can have unintended consequences. Feline obesity is on the rise, impacting the health, longevity, and wellbeing of cats. A new study from the University of Illinois Urbana-Champaign looks at what happens in the digestive system and gut microbiota when cats eat too much.

“About 60% of cats in the U.S. are overweight, which can lead to health problems such as diabetes and chronic inflammation. While many studies have investigated feline weight loss, there has been little focus on the opposite process, which is also important. In this study, we wanted to learn more about the metabolic and gastrointestinal changes that occur as a result of overeating and weight gain in cats,” says study co-author Kelly Swanson, professor in the Department of Animal Sciences and interim director of the Division of Nutritional Sciences (DNS), part of the College of Agricultural, Consumer and Environmental Sciences (ACES) at U. of I.

The study included 11 adult spayed female cats. They were fed a standard dry cat food and after two weeks of baseline measurements, they were allowed to eat as much as they wanted. The researchers collected blood and fecal samples at regular intervals and monitored physical activity.

Once the cats were able to overeat, they immediately increased their food intake substantially and started to gain weight. At the onset of the study, their average body condition score (BCS) was 5.41 on a 9-point scale. After 18 weeks of overfeeding, it had increased to 8.27, corresponding to being 30% overweight. BCS is equivalent to body mass index (BMI) for humans, and 6 or above is considered overweight, Swanson said.

The researchers analyzed changes in fecal output, gastrointestinal transit time, digestive efficiency (nutrient digestibility), and microbiota bacterial composition over the 20-week duration of the study.

“We found that as cats ate more and gained weight, gastrointestinal transit time was reduced, and so was digestive efficiency. When the body gets less food, it will be more efficient in extracting nutrients. But when the amount of food increases, it passes through the digestive system faster and fewer nutrients are extracted in the process,” Swanson explained.  

The researchers also found significant changes in gut microbial composition between the lean cats at baseline and after 18 weeks of weight gain. The relative abundance of Bifidobacterium, which has antimicrobial activity, inhibits pathogens, and stimulates the immune system, increased, while Collinsella, which degrades fiber and has been linked to pro-inflammatory diseases, decreased. These results are opposite to what has been measured in overweight humans and suggest that their association to weight gain is complex, Swanson noted.   

“The change in the gastrointestinal transit time was a novel finding and a potential reason for the change in fecal microbiota. Future studies should consider measuring transit time to better explain modifications to the microbiome of pets,” he added. 

As the cats’ food consumption grew, so did their fecal output. In other words, as they ate more, they also pooped more. At the same time, fecal pH decreased, meaning that the stool became more acidic.

“In humans, a low fecal pH indicates poor absorption of carbohydrates and fat. Our findings correlate with this, as reduced fecal pH aligned with higher food intake and reduced digestibility,” Swanson said.

The researchers also measured the cats’ activity level with a monitor attached to a collar. The cats were housed in a group setting where they were able to interact with each other and play with toys, except for the days when stool samples were collected.

“We expected that weight gain might lead to decreased physical activity, but we did not observe any consistent changes in activity level. However, this could vary with individual cats and their environment, and how much their owners interact with them,” Swanson stated.

Understanding the metabolic and gastrointestinal changes that occur with weight gain and obesity in pets may help with future prevention and treatment plans, the researchers conclude.

Pet owners who want to help their cats lose weight can employ various strategies. In another new study, Swanson and his co-authors showed that restricted feeding can promote safe weight and fat loss in cats. The researchers also suggest pet parents encourage activity in their feline companions. For example, they can stimulate foraging by placing food around the home, or use food puzzles during mealtime to promote engagement and mental enrichment.

After the conclusion of the weight gain study, the 11 cats were put on a restricted-feeding diet that helped them return to normal weight.

The first study, “Effects of overfeeding on the digestive efficiency, voluntary physical activity levels, and fecal characteristics and microbiota of adult cats,” is published in the Journal of Animal Science [DOI: 10.1093/jas/skad338]. Authors are Danielle Opetz, Patricia Oba, and Kelly Swanson. Funding was provided by the USDA National Institute of Food and Agriculture (Hatch Grant #ILLU-538–937).

The second study, “Effects of weight loss and feeding specially formulated diets on the body composition, blood metabolite profiles, voluntary physical activity, and fecal metabolites and microbiota of overweight cats,” is also published in the Journal of Animal Science [DOI: 10.1093/jas/skad332]. Authors are Danielle Opetz, Patricia Oba, Darcia Kostiuk, Janelle Kelly, and Kelly Swanson. The funding for this study was provided by Champion Petfoods Holding, Inc., Edmonton, Canada.

 

Study reveals untapped potential to increase eye donations needed for sight-restoring surgeries

Peer-Reviewed Publication

UNIVERSITY OF SOUTHAMPTON

Eye after cornea transplant 

IMAGE: 

EYE AFTER CORNEA TRANSPLANT.

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CREDIT: MUST CREDIT NHS BLOOD AND TRANSPLANT




  • New research highlights the need for routine discussions about eye donation in end-of-life care clinical settings
  • Less than four per cent of eligible patients in end-of-life care settings were asked to consider eye donation
  • Patients had positive views about eye donation, but most did not know it could be an option for them
  • Staff need training and guidance to support discussing eye donation with patients

A new study has found there is significant scope to increase the number of eye donations from patients cared for in hospice and palliative care settings - donations which are desperately needed for sight-restoring surgeries.

Researchers from the University of Southampton and clinical partners, including NHS Blood and Transplant, carried out the study, which has been funded by the National Institute for Health and Care Research (NIHR). It found just a small fraction of eligible patients in hospice and palliative care settings are being approached to consider the option of eye donation. This is despite both healthcare professionals and patients having favourable views towards it.

The researchers say practice needs to change so that patients who wish to donate are being offered the opportunity as a part of routine end-of-life care.

Demand for eye tissue

Over two million people in the UK are living with sight loss, taking a huge toll on their lives and costing the economy a reported £4.34 billion each year. Some conditions, such as Keratoconus and Fuchs’ Corneal Dystrophy, can be treated with surgery which removes all or part of a damaged cornea and replaces it with healthy donor tissue (corneal transplant). But there is a shortfall in the supply of donor tissue needed for operations.

NHS Blood and Transplant aims to achieve a weekly stock of 350 eyes for use in surgery or research. But from April 2021 to March 2022, only 88 eyes on average were donated per week.

The RNIB predicts that by 2050, the number of people with sight loss will double to nearly four million (mainly due to the ageing population), further increasing the demand for eye tissue. Each donor can help restore or improve the sight of up to 10 people.

‘Many potential donors’

Clinical partners across England reviewed the case notes of 1,199 deceased patients in three hospice care and three hospital-based palliative care services.

Although 46 per cent of patients were eligible to donate their eyes, less than 4 per cent of potential donors had been approached or referred for eye donation.

Views on donation

To understand attitudes and potential barriers to eye donation, the researchers interviewed over 100 healthcare professionals and over 60 patients and carers receiving palliative care. They also conducted a national survey of 156 service providers.

Dr Tracy Long-Sutehall, Associate Professor at the University of Southampton and lead author of the research which has been published today [3 November] in the Health and Social Care Delivery Research Journal, says:

“Many patients and carers were not aware of eye donation being an option for themselves or their relative. Those we spoke to generally had positive views about eye donation and were open to being asked about their preferences. This suggests there could be many potential donors in hospice and palliative care settings who are willing to donate their eyes after their death so that others might see.”

Knowledge gap

Healthcare professionals were in favour of eye donation being discussed as part of end-of-life care planning but had gaps in their knowledge around eligibility criteria and processes for referral; more than half had received no formal training regarding eye donation. As such, the majority had never, or hardly ever, initiated a discussion about eye donation with patients or family members.

Dr Long-Sutehall added: “Conversations around eye donation need to be sensitively managed, so it’s understandable that healthcare professionals would be reluctant to raise it if they haven’t had suitable training and education.”

Future opportunities

The study demonstrates that there is significant potential for more patients to be given the opportunity to donate their eyes in the future, and for eye donation to be embedded in routine end-of-life care clinical practice.

Emma Winstanley, Lead Nurse for Tissue and Eye Services at NHS Blood and Transplant who was a co-applicant on the study, says:

“This research provides crucial new insight to better understand both patient and healthcare staff views on eye donation. With more patients dying outside of traditional hospital settings, either at home or in hospices, it is essential that patients have the opportunity to donate whenever donation is possible. Eye donation is particularly special as donation can even be possible for patients who have cancer. We know that many patients and families take great comfort and pride from donation. By working closely with hospice colleagues, we can enable more patients to donate and more life-transforming surgeries to take place.”

The researchers highlight several implications for service development, healthcare practice and recommendations for further research, including the evaluation of a Support Toolkit for Eye donation in Palliative care Settings (STEPS) developed by the research team.

Eye Donation from Palliative and Hospice care contexts: the EDiPPPP mixed methods study was funded by the NIHR Health and Social Care Delivery Research programme.

Ends

​​​​​Placido disk reflected off eye with keratoconus.

CREDIT

National Keratoconus Foundation


Contact

Steve Williams, Media Relations, University of Southampton press@soton.ac.uk or 023 8059 3212.

Notes for editors

  1. Eye Donation from Palliative and Hospice care contexts: the EDiPPPP mixed methods study is published in the Health and Social Care Delivery Research Journal and is available to download here: Eye donation from palliative and hospice care contexts: the EDiPPPP mixed-methods study (nihr.ac.uk)
  2. Interview opportunities
    1. Dr Tracy Long-Sutehall, Associate Professor at the University of Southampton and lead investigator on the EDiPPPP study. (Southampton)
    2. Dr Sarah Mollart Consultant in Palliative Medicine at St Nicholas Hospice and clinical investigator on the EDiPPPP study. (Bury St Edmunds, Suffolk)
    3. Laura – Mum of two who has had two corneal transplants for an undiagnosed illness. This has allowed her to see her children grow up. Her mother has also had a corneal transplant. (London)
    4. Angie – Hospice nurse who made the decision (along with her mum and sister) to donate her father William’s corneas, kidneys and heart valves. The hospice she works at promotes discussion about organ donation (including corneas). (Wolverhampton)
  3. Images available to download here: https://safesend.soton.ac.uk/pickup?claimID=ANs4m4SFgmFFfuBh&claimPasscode=a9JAjbHmcAcnCzcC
    1. Placido disk reflected off eye with keratoconus - Credit National Keratoconus Foundation
    2. Eye after cornea transplant - Credit NHS Blood and Transplant

Additional information

The University of Southampton drives original thinking, turns knowledge into action and impact, and creates solutions to the world’s challenges. We are among the top 100 institutions globally (QS World University Rankings 2023). Our academics are leaders in their fields, forging links with high-profile international businesses and organisations, and inspiring a 22,000-strong community of exceptional students, from over 135 countries worldwide. Through our high-quality education, the University helps students on a journey of discovery to realise their potential and join our global network of over 200,000 alumni. www.southampton.ac.uk

www.southampton.ac.uk/news/contact-press-team.page

Follow us on twitter: https://twitter.com/UoSMedia

 

About the National Institute for Health and Care Research (NIHR)

  • The mission of the National Institute for Health and Care Research (NIHR) is to improve the health and wealth of the nation through research. We do this by:
  • Funding high quality, timely research that benefits the NHS, public health and social care;
  • Investing in world-class expertise, facilities and a skilled delivery workforce to translate discoveries into improved treatments and services;
  • Partnering with patients, service users, carers and communities, improving the relevance, quality and impact of our research;
  • Attracting, training and supporting the best researchers to tackle complex health and social care challenges;
  • Collaborating with other public funders, charities and industry to help shape a cohesive and globally competitive research system;
  • Funding applied global health research and training to meet the needs of the poorest people in low and middle income countries.

NIHR is funded by the Department of Health and Social Care. Its work in low-and-middle-income countries is principally funded through UK Aid from the UK government.

A.I.

Contrary to common belief, artificial intelligence will not put you out of work


New research unveils the complex nature of human-AI interactions: AI favors junior workers, but not for the reasons you'd expect

Peer-Reviewed Publication

INSTITUTE FOR OPERATIONS RESEARCH AND THE MANAGEMENT SCIENCES





INFORMS Journal Management Science New Study Key Takeaways:

  • While AI benefits workers with greater task-based experience, senior workers gain less from AI due to lower trust in AI.
  • Lower trust is likely triggered by the senior workers’ broader job responsibilities.
  • Employers should consider different worker experience levels and experience types when evaluating job performance in roles that require teaming with AI.

 

BALTIMORE, MD, November 2, 2023 – New research in the INFORMS journal Management Science is providing insights for business leaders on how work experience affects employees interacting with AI.

The study, “Friend or Foe? Teaming Between Artificial Intelligence and Workers with Variation in Experience,” looks at the influence of two major types of human work experience (narrow experience based on the specific task volume and broad experience based on seniority) on the human-AI team dynamics.

“We developed an AI solution for medical chart coding in a publicly traded company and conducted a field study among the knowledge workers,” says Weiguang Wang of the University of Rochester and leading author of the study. “We were surprised by what we found in the study. The different dimensions of work experience have distinct interactions with AI and play unique roles in human-AI teaming.”

“While one might think that less experienced workers should benefit more from the help of AI, we find the opposite – AI benefits workers with greater task-based experience. At the same time, senior workers, despite their greater experience, gain less from AI than their junior colleagues,” says Guodong (Gordon) Gao of Johns Hopkins Carey Business School, and study co-author.

Further investigation reveals that the relatively lower productivity lift from AI is not a result of seniority per se but rather their higher sensitivity to the imperfection of AI, which lowers their trust in AI.

“This finding presents a dilemma: Employees with greater experience are in a better position to leverage AI for productivity, but the senior employees who assume greater responsibilities and care about the organization tend to shy away from AI because they see the risks of relying on AI’s assistance. As a result, they are not effectively leveraging AI,” says Ritu Agarwal of Johns Hopkins Carey Business School, a co-author of the study.

The researchers urge employers to carefully consider different worker experience types and levels when introducing AI into the work. New workers with less task experience are disadvantaged in leveraging AI. Meanwhile, senior workers with more organizational experience may be concerned about the potential risks imposed by AI. Addressing these unique challenges are key to productive human-AI teaming.

 

Link to full study.

 

About INFORMS and Management Science

Management Science is a premier peer-reviewed scholarly journal focused on research using quantitative approaches to study all aspects of management in companies and organizations. It is published by INFORMS, the leading international association for data and decision science professionals. More information is available at www.informs.org or @informs.

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AI trained to identify least green homes by Cambridge researchers


Peer-Reviewed Publication

UNIVERSITY OF CAMBRIDGE

Street view images of houses from the study 

IMAGE: 

STREET VIEW IMAGES OF HOUSES IN CAMBRIDGE, UK, IDENTIFYING BUILDING FEATURES. RED REPRESENTS REGION CONTRIBUTING MOST TO THE 'HARD-TO-DECARBONIZE' IDENTIFICATION. BLUE REPRESENTS LOW CONTRIBUTION.

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CREDIT: RONITA BARDHAN




University of Cambridge media release

 

First of its kind AI-model can help policy-makers efficiently identify and prioritize houses for retrofitting and other decarbonizing measures.

 

FOR IMMEDIATE RELEASE

 

  • Model identified ‘hard to decarbonize’ houses with 90% precision and additional data will improve this.
  • Model trained with open source data including from energy performance certificates, and street and aerial view images. It could be used anywhere in the world.
  • Model can even identify specific parts of houses losing most heat, including roofs and windows.

‘Hard-to-decarbonize’ (HtD) houses are responsible for over a quarter of all direct housing emissions – a major obstacle to achieving net zero – but are rarely identified or targeted for improvement.

Now a new ‘deep learning’ model trained by researchers from Cambridge University’s Department of Architecture promises to make it far easier, faster and cheaper to identify these high priority problem properties and develop strategies to improve their green credentials.

Houses can be ‘hard to decarbonize’ for various reasons including their age, structure, location, social-economic barriers and availability of data. Policymakers have tended to focus mostly on generic buildings or specific hard-to-decarbonise technologies but the study, published in the journal Sustainable Cities and Society, could help to change this.

Maoran Sun, an urban researcher and data scientist, and his PhD supervisor Dr Ronita Bardhan, who leads Cambridge’s Sustainable Design Group, show that their AI model can classify HtD houses with 90% precision and expect this to rise as they add more data, work which is already underway.

Dr Bardhan said: “This is the first time that AI has been trained to identify hard-to-decarbonize buildings using open source data to achieve this.

“Policymakers need to know how many houses they have to decarbonize, but they often lack the resources to perform detail audits on every house. Our model can direct them to high priority houses, saving them precious time and resources.”

The model also helps authorities to understand the geographical distribution of HtD houses, enabling them to efficiently target and deploy interventions efficiently.

The researchers trained their AI model using data for their home city of Cambridge, in the United Kingdom. They fed in data from Energy Performance Certificates (EPCs) as well as data from street view images, aerial view images, land surface temperature and building stock. In total, their model identified 700 HtD houses and 635 non-HtD houses. All of the data used was open source.

Maoran Sun said: “We trained our model using the limited EPC data which was available. Now the model can predict for the city’s other houses without the need for any EPC data.”

Bardhan added: “This data is available freely and our model can even be used in countries where datasets are very patchy. The framework enables users to feed in multi-source datasets for identification of HtD houses.”

Sun and Bardhan are now working on an even more advanced framework which will bring additional data layers relating to factors including energy use, poverty levels and thermal images of building facades. They expect this to increase the model’s accuracy but also to provide even more detailed information.

The model is already capable of identifying specific parts of buildings, such as roofs and windows, which are losing most heat, and whether a building is old or modern. But the researchers are confident they can significantly increase detail and accuracy.

They are already training AI models based on other UK cities using thermal images of buildings, and are collaborating with a space products-based organisation to benefit from higher resolution thermal images from new satellites. Bardhan has been part of the NSIP – UK Space Agency program where she collaborated with the Department of Astronomy and Cambridge Zero on using high resolution thermal infrared space telescopes for globally monitoring the energy efficiency of buildings.

Sun said: “Our models will increasingly help residents and authorities to target retrofitting interventions to particular building features like walls, windows and other elements.”

Bardhan explains that, until now, decarbonization policy decisions have been based on evidence derived from limited datasets, but is optimistic about AI’s power to change this.

“We can now deal with far larger datasets. Moving forward with climate change, we need adaptation strategies based on evidence of the kind provided by our model. Even very simple street view photographs can offer a wealth of information without putting anyone at risk.”

The researchers argue that by making data more visible and accessible to the public, it will become much easier to build consensus around efforts to achieve net zero.

“Empowering people with their own data makes it much easier for them to negotiate for support,” Bardhan said.

She added: “There is a lot of talk about the need for specialised skills to achieve decarbonisation but these are simple data sets and we can make this model very user friendly and accessible for the authorities and individual residents.”

Aerial view images of houses in Cambridge, UK. Red represents region contributing most to the Hard to decarbonize identification. Blue represents low contribution.

CREDIT

Ronita Bardhan

Cambridge as a study site

Cambridge is an atypical city but informative site on which to base the initial model. Bardhan notes that Cambridge is relatively affluent meaning that there is a greater willingness and financial ability to decarbonize houses.

“Cambridge isn’t ‘hard to reach’ for decarbonisation in that sense,” Bardhan said. “But the city’s housing stock is quite old and building bylaws prevent retrofitting and the use of modern materials in some of the more historically important properties. So it faces interesting challenges.”

The researchers will discuss their findings with Cambridge City Council. Bardhan previously worked with the Council to assess council houses for heat loss. They will also continue to work with colleagues at Cambridge Zero and the University’s Decarbonisation Network.

Reference

M. Sun & R. Bardhan, ‘Identifying Hard-to-Decarbonize houses from multi-source data in Cambridge, UK’, Sustainable Cities and Society (2023). DOI: 10.1016/j.scs.2023.105015

Media contacts

Tom Almeroth-Williams, Communications Manager (Research), University of Cambridge: researchcommunications@admin.cam.ac.uk  / tel: +44 (0) 7540 139 444

Ronita Bardhan, University of Cambridge: rb867@cam.ac.uk